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Paper Citation Record · LEDGER

Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2006.12097.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2006.12097 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:42:26.819526Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T04:47:37.944454Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e100c499-09c1-4e98-88ff-d4ca807d9427 · inbound

Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection cites this paper.

Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T23:02:02.941870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:02:02.941870Z digest=sha256:cc057d5c8105c1500cfda5762be8df33ad249f4a15fe000627ccda937f2b453c

Observation 90e36753-0b1f-4514-9616-6bda8b2a6414 · inbound

Diffusion Model-Based Data Synthesis Aided Federated Semi-Supervised Learning cites this paper.

Diffusion Model-Based Data Synthesis Aided Federated Semi-Supervised Learning Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T22:18:46.859621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:18:46.859621Z digest=sha256:aa44bbf606e80d9f614d203be879656d753ad7acf555eadcaaceb14eb6dd8fd3

Observation ff196041-2a38-4289-bf4a-90c673c10ad0 · inbound

A Survey on Federated Learning in Human Sensing cites this paper.

A Survey on Federated Learning in Human Sensing Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 113

Resolution
unresolved
no resolver link, observed 2026-08-10T21:43:59.035479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:43:59.035479Z digest=sha256:4fbae8e7bc1dcd3b3f2f6061f280612589ded8c25c0f47d7a15e2e03b48ab1e1

Observation 7dc2e81c-8c68-4983-9685-61c1ce512e19 · inbound

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things cites this paper.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.819526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.819526Z digest=sha256:bc7a7d0c168b1082ca10dcb02e32fbba0cd8857398f1c850c1e980558d619cc1

Observation 6da8a05e-3f66-43f9-8cb7-2d0179e87e40 · inbound

Unified Alignment Protocol: Making Sense of the Unlabeled Data in New Domains cites this paper.

Unified Alignment Protocol: Making Sense of the Unlabeled Data in New Domains Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T13:47:09.188087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:47:09.188087Z digest=sha256:5579545d93a7374e82c28765a535c05d7ab05ff4d40423159e92d6aa71e0461a

Observation 779a73dc-1f17-4387-8836-53b12964f197 · inbound

Closing the Alignment-Maturity Gap in Federated Prototype Learning cites this paper.

Closing the Alignment-Maturity Gap in Federated Prototype Learning Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:56:16.401559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T15:55:11.018371Z digest=sha256:154055f00f21b6a2c572391219feb5f038794b0c4d32bee109d6c5a5fc60c57e

Observation 2061973a-8226-47ce-81c8-dc064731d453 · inbound

Accurate and Resource-Efficient Federated Continual Learning cites this paper.

Accurate and Resource-Efficient Federated Continual Learning Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-03T04:47:37.945941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-27T13:40:35.795292Z digest=sha256:13df1c3dc83a10cdeeb615bfa3950d08d7e942da164e4771c789ad8e9ce66f05